Character recognition for overlapping textual user input

ABSTRACT

Techniques described herein may recognize handwritten characters that are written at least partially over the top of one another that are input to a computing device. The handwritten characters may be formed of one or more strokes. A user may write characters or parts of words over approximately the same area of graphical user interface (i.e., on top of each other) without having to wait for a timeout between character input and without having to select a button or provide another input indicating the character is complete before entering input for another character. Once a character is at least partially recognized, a graphical indication corresponding to the user input displayed on a screen may be altered. Such alterations may include fading or changing size or location of the graphical indication.

This application is a continuation of U.S. application Ser. No.13/158,795, filed, Jun. 13, 2011, the entire content of which isincorporated herein by reference.

TECHNICAL FIELD

The disclosure relates to character recognition for overlapping textualuser input.

BACKGROUND

Users may often interact with computing devices such as mobile phones,personal data assistants (PDAs), desktop computers, signature pads,tablet computers, or other mobile devices via a touch-sensitive inputdevices, for example, touch-sensitive screens. Typical touch-sensitivescreens (generally referred to herein as “touch screens”) allow a userto input text via writing on the screen using, for example, a stylus orfinger. Some touch screens, especially those in smaller devices, have alimited area in which to write. Typical character recognition softwaredifferentiates one character from another through redefining writtencharacters so they are drawn in a single stroke, requiring a user towait a timeout period before writing a second character, or usinghorizontal offset between characters.

SUMMARY

In one example, a method for recognizing characters is provided. Themethod comprises receiving touch-based input relating to a sequence ofstrokes at a touch-based interface of a computing device, wherein afirst subset of the sequence of strokes corresponds to a first area ofthe touch-based interface and a second subset of the sequence of strokescorresponds to a second area of the touch-based interface that at leastpartially overlaps the first area. The method further comprisesdisplaying a graphical representation of the first subset of thesequence of strokes on an output device coupled to the computing deviceand determining a confidence level that a first character approximatelymatches the first subset of the sequence of strokes, wherein theconfidence level is of at least a first confidence threshold. The methodalso comprises altering the display of the graphical representation ofthe first subset of the sequence of strokes based on the confidencelevel and providing the first character for processing by an applicationexecuting on the computing device when the confidence level is of atleast a second confidence threshold, wherein the application is designedto process characters from touch-based input.

In another example, a tangible computer-readable medium is provided thatcomprises instructions for causing a programmable processor to performoperations. The instructions may include receiving touch-based inputrelating to a sequence of strokes at a touch-based interface of acomputing device, wherein a first subset of the sequence of strokescorresponds to a first graphical area of the touch-based interface and asecond subset of the sequence of strokes corresponds to a secondgraphical area of the touch-based interface that at least partiallyoverlaps the first graphical area. The instructions may also includedisplaying a graphical representation of the first subset of thesequence of strokes on an output device coupled to the computing deviceand determining that the first subset of the sequence of strokescorresponds to a first character by at least a first confidencethreshold. The instructions may also include altering the graphicalrepresentation of the first subset of the sequence of strokes based onthe determination that the first subset of the sequence of strokescorresponds to the first character. The instructions may includeproviding the first character for processing by an application executingon the computing device, wherein the application is designed to processcharacters from touch-based input.

In yet another example, a computing device comprising one or moreprocessors is provided. The computing device may further comprise aninput device to receive touch-based user input of a sequence of strokesrelated to textual information, wherein the sequence of strokescomprises a first subset of strokes corresponding to a first area of theinput device and a second subset of strokes corresponding to a secondarea of the input device at least partially overlapping the first subsetof strokes. The computing device may also comprise means for determiningwhich strokes of the series of stroke fall into the first subset of thesequence of strokes and for determining that the first subset of thesequence of strokes corresponds to a first character. The computingdevice may further comprise an output device to display a graphicalrepresentation of the first subset of the sequence of strokes, whereinthe output device alters the graphical representation based on thedetermination that the first subset of the sequence of strokescorresponds to the first character, wherein the output device furtheroutput the first character.

The details of one or more aspects of the disclosure are set forth inthe accompanying drawings and the description below. Other features,objects, and advantages of the disclosure will be apparent from thedescription and drawings, and from the claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram illustrating an example of a computing devicethat may execute one or more applications and receive a user input, inaccordance with one or more aspects of the present disclosure.

FIG. 2 is a block diagram illustrating further details of one example ofthe computing device shown in FIG. 1, in accordance with one or moreaspects of the present disclosure.

FIG. 3 is a flow chart illustrating an example method that may beperformed by a computing device to recognize a character correspondingto a touch input, in accordance with one or more aspects of the presentdisclosure.

FIG. 4 is a conceptual diagram illustrating one example of a sequence ofstrokes of touch-based input that may be recognized by a computingdevice executing a character recognition module, in accordance with oneor more aspects of the present disclosure.

FIGS. 5A-5D are conceptual diagrams illustrating one example of asequence of strokes inputted by a user that may be analyzed by acharacter recognition module, in accordance with one or more aspects ofthe present disclosure.

In accordance with common practice, the various described features arenot drawn to scale and are drawn to emphasize features relevant to thepresent disclosure. Like reference characters denote like elementsthroughout the figures and text.

DETAILED DESCRIPTION

Techniques of the present disclosure allow a computing device torecognize handwritten characters that are written at least partiallyover the top of one another. A user of the computing device inputshandwritten characters through input (e.g., touch input) formed of oneor more strokes. A character may be any marking that conveysinformation, such as, but not limited to, letters, numbers, or othersymbols.

A user may continuously write characters or parts of words overapproximately the same area of the screen (i.e., on top of each other)without having to wait for a timeout between character input and withouthaving to select a button or provide another input indicating thecharacter is complete before entering input for another character. Agraphical indication on the screen corresponding to the user input(referred to herein as “ink”) may be displayed.

The computing device may have a character recognition module thatautomatically separates the characters from one another. Potentiallyrecognized characters may have a confidence level that indicates thelevel of accuracy with which the potentially recognized charactercorresponds to the user input. Once a character is recognized with aconfidence level above a first confidence threshold, the graphicalrepresentation of the user input corresponding to that recognizedcharacter may be displayed with a property indicating that the characterwas recognized from the user input (e.g., at least partially faded).Once a character is recognized with a confidence level above a secondconfidence threshold, the recognition module may generate, identify, orprovide the character corresponding to that input for use by anotherapplication. When the character is recognized with a confidence levelabove the second confidence level, the graphical representation of therecognized character may be removed from the display. In some examples,the computing device displays those characters that are recognized astext. The techniques described herein may also be applied on a basisother than individual characters, such as words or sentences.

FIG. 1 is a block diagram illustrating an example of a computing device2 that may execute one or more applications (e.g., text entryapplication 8) and receive a user input 18, in accordance with one ormore aspects of the present disclosure. Computing device 2 may, in someexamples, include, be, or be a part of a portable computing device(e.g., a mobile phone, netbook, laptop, personal data assistant (PDA),or tablet device) or a stationary computer (e.g., a desktop computer),or may be another computing device, such as a signature pad. Computingdevice 2 may also connect to a network including a wired or wirelessnetwork. One example of computing device 2 is more fully described inFIG. 2, discussed below.

Computing device 2 may include an input/output (“I/O”) device 12 such asa presence-sensitive device capable of receiving user input 18 from auser 14, such as, for example, detecting gestures. In one example, I/Odevice 12 is a touch-sensitive device (e.g., touch screen, track pad,track point, or the like) capable of receiving user input 18 from user14, wherein user input 18 is touch input. I/O device 12 may, in oneexample, generate one or more signals corresponding to the coordinatesof a position touched on I/O device 12. These signals may be provided asinformation to components of computing device 2 (e.g., text entryapplication 8 in FIG. 1, processor 30, or operating system 44 in FIG.2). I/O device 12 may also display or otherwise output (e.g., auditory)information to user 14. For example, I/O device 12 may display acharacter 22 or a cursor 24. I/O device 12 may in other examples displayvideo or other graphical information. I/O device 12 may provide numerousforms of output information to user 14, which are further discussed inFIG. 2.

In some examples, I/O device 12 may comprise a touch-based interface 4and a display device 20. In some examples, touch-based interface 4 anddisplay device 20 may be integrated into a single device, for example, atouch screen. In another example, touch-based interface 4 and displaydevice 20 may be separate devices, for example, touch-based interface 4may be a touch pad or track point and display device 20 may be a liquidcrystal display (“LCD”).

User 14 may interact with I/O device 12, for example, a touch-sensitivescreen, by performing user input 18 on I/O device 12. For example, user14 may handwrite user input 18 onto the I/O device 12. When user 14inputs handwriting, the user input 18 may be in print, cursive, or anyother form of writing or drawing.

User input 18 may include one or more gestures performed by user 14.User 14 may perform user input 18 by placing one or more fingers oranother implement, such as a stylus 15, in contact with I/O device 12,which may be a touch-sensitive screen. Stylus 15 may be any device thataids user 14 in handwriting on the touch-based interface 4. In oneexample, user 14 may move one or more fingers while in contact withtouch-based interface 4. User input 18 may be handwritten and associatedwith a character from a natural language. Characters from a naturallanguage may include numbers, letters, symbols, or other indicia capableof communicating meaning either independently or in combination withother characters. In one example, a set of characters containscharacters from a natural language.

For example, user 14 may handwrite on touch-based interface 4 in one ormore strokes. As used herein, a stroke may be any portion of a single,unbroken movement that is received by the touch-based interface 4. Forillustrative purposes, strokes herein are described mostly in terms ofsingle movements or single characters; however, it is to be understoodthat a stroke may be an entire movement or may be a fragment or portionof an entire movement, and may be a part of a character, a wholecharacter, or more than one character. In the example of FIG. 1, user 14begins to handwrite the word “Hello” on the touch-based interface 4. Todo so, user 14 may handwrite a sequence of strokes 19-1 through 19-4 viathe touch-based interface 4. User 14 handwrites a first stroke 19-1 fora vertical line corresponding to the left side of the “H,” then begins asecond stroke 19-2 for a horizontal bar for the “H.” User 14 completesthe “H” by writing the third stroke 19-3, which is another verticalline. Next, the user 14 writes stroke 19-4 for the “el” in “Hello.” The“e” corresponds to a first portion of stroke 19-4 and the “l”corresponds to a second portion of stroke 19-4.

I/O device 12 may generate a signal corresponding to user input 18 thatis transmitted to user input module 6. User input module 6 may processuser input 18 received from user 14. In some cases, user input module 6may perform additional processing of user input 18, such as, forexample, converting user input 18 into more usable forms. In someexamples, user input module 6 provides a signal to display device 20 todisplay a graphical representation of user input 18. For example, asuser 14 writes strokes 19-1 through 19-4 on the touch-based interface 4,display device 20 displays ink corresponding to the user input 18. Insome cases, user input module 6 may transmit a signal corresponding touser input 18 to an application, such as text entry application 8, or toanother component in computing device 2. Text entry application 8 may beany application that accepts textual user input, such as, for example, aword processing application, an Internet browser, an application thatmay be controlled with textual user input, or the like. In someexamples, user input module 6 may determine a duration of user input 18or any duration between receiving one stroke and receiving anotherstroke. For example, input module 6 may measure the period of timebetween two strokes to distinguish between, for example, a singlecharacter and a word.

In some examples, text entry application 8 may include a characterrecognition module 10. Character recognition module 10 may perform arecognition operation on the signal corresponding to user input 18. Therecognition operation may determine a character, for example, character22, corresponding to at least a portion of user input 18. In oneexample, the recognition operation may analyze user input 18 todetermine whether any portion of user input 18 corresponds to one ormore characters. Character recognition module 10 may assign a score orranking to potential character matches for a portion of user input 18.The score or ranking is a measure of how likely it is that a stroke orsequence of strokes corresponds to a particular character. Characterrecognition module 10 may select a character from the potentialcharacter matches based at least in part on the score or ranking, aswell as other factors. In one example, character recognition module 10may select a character corresponding to a portion of user input 18 whenthat character has a score above a selected threshold level. In someexamples, character recognition module 10 may perform some or all of thefunctions of user input module 6. Some example methods of characterrecognition are described herein. In other examples, characterrecognition module 10 may additionally perform any method or have anyfeature of other character recognition operations and methods now knownor later developed. The techniques described herein generally arediscussed in terms of characters; however, the techniques describedherein may also apply to words, sentences, or other groupings ofcharacters. For example, character recognition module 10 may recognizeone or more words that are partially overlapping other words orcharacters.

For example, character recognition module 10 may access referencedatabase 11 when analyzing user input 18. Reference database 11 maycontain a table of characters, a dictionary, and/or a grammar reference.For example, character recognition module 10 may perform a lookup inreference database 11 based at least in part on user input 18, wherereference database 11 contains a table mappings characters with one ormore strokes. In another example, character recognition module 10 mayperform a lookup of a potential word in reference database 11 to assistrecognizing a character based at least in part on that character'srelationship to previously recognized characters. For example, ifcharacter recognition module 10 previously recognized five characters asO, R, A, N, and G, there is a higher probability that a sixth characteris a letter E based on the “ORANG” preceding the sixth character,spelling “ORANGE.” Therefore, character recognition module 10 may givethe letter E a higher rank for the sixth character than the rank forother characters. Similarly, character recognition module 10 may use agrammar reference in reference database 11 to rank characters or wordsbased at least partially on grammatical rules. Character recognitionmodule 10 may further determine a character of a subset of strokes basedon the relationship of that subset of strokes to another character (forexample, the subset of strokes is the next letter in a word or is thenext word of a sentence).

In the example of FIG. 1, character recognition module 10 has recognizedstrokes 19-1 through 19-3, shown as recognized input 26, correspondingto the letter “H.” Character recognition module 10 may generate a signalcorresponding to the recognized input 26 and provide it to text entryapplication 8 or to another component or module within computing device2. For example, character recognition module 10 may provide text entryapplication 8 with a signal indicating that user 14 has inputted theletter “H.” Text entry application 8 may generate a signal correspondingto the letter “H” for further processing by text entry application 8 orcomputing device 2. In one example, text entry application 8 displaysrecognized input 26 on display device 20. For example, display device 20may display character 22 representing recognized input 26 at a locationof cursor 24. Also, cursor 24 or any other text may be repositioned dueto the addition of character 22.

In another example, character recognition module 10 instructs I/O device12 to cease displaying and/or modify the display of any previouslydisplayed graphical representation of recognized input 26. That is,display device 20 may alter the ink corresponding to recognized input 26once character recognition module 10 recognizes that portion of userinput 18. For example, the ink corresponding to recognized input 26 mayfade out. In another example, display device 20 may display recognizedinput 26 in a different location, a different color, a different font,or may change font qualities (e.g., bold, underline, or italicize) orsize, or may alter any other attribute of the ink once recognized input26 is recognized (for example, display recognized input 26 as anoutline). In other examples, older strokes may be slowly faded out withtime, shifted off to the side, change in size, or otherwise change inorder to clear display device 20 based at least in part on a confidencelevel that the strokes are accurately recognized. In one example,strokes that are recognized with a confidence level above at least asecond threshold level are completely faded from display device 20.

In the example shown in FIG. 1, character recognition module 10 has notyet recognized another portion of user input 18, that is, unrecognizedinput 28. Display device 20 may display a graphical representation ofunrecognized input 28 (for example, in ink). In one example, displaydevice 20 may display unrecognized input 28 in a different style inkthan recognized input 26 (for example, in a different color, differentline thickness, different transparency, etc.). Once characterrecognition module 10 recognizes unrecognized input 28 by a least afirst threshold confidence level, display device 20 may displayunrecognized input 28 as recognized input 26 is displayed.

In one example, computing device 2 is a mobile device having atouch-based interface 4 with a limited graphical area. Techniquesdescribed herein enable user 14 to more efficiently use the touch-basedinterface 4 for handwritten user input. In other examples, computingdevice 2 is a desktop machine. In such examples, user 14 may inputhandwriting to provide, for example, input into a field of a web page.

FIG. 2 is a block diagram illustrating further details of one example ofcomputing device 2 shown in FIG. 1. FIG. 2 illustrates only oneparticular example of computing device 2, and many other exampleembodiments of computing device 2 may be used in other instances.

As shown in the specific example of FIG. 2, computing device 2 includesone or more processors 30, memory 32, a network interface 34, one ormore storage devices 36, one or more input devices 38, one or moreoutput devices 40, and one or more batteries or other power sources 42.Computing device 2 also includes an operating system 44, which mayinclude user input module 6 executable by computing device 2. Computingdevice 2 may include one or more applications 46 and text entryapplication 8, which may include character mapping module 10 executableby computing device 2. Operating system 44, application 46 and textentry application 8 are also executable by computing device 2. Each ofcomponents 30, 32, 34, 36, 38, 40, 42, 44, 46, 6, 8, and 10 may beinterconnected (physically, communicatively, and/or operatively) forinter-component communications.

Processors 30 may be configured to implement functionality and/orprocess instructions for execution in computing device 2. Processors 30may be capable of processing instructions stored in memory 32 orinstructions stored on storage devices 36.

Memory 32 may be configured to store information within computing device2 during operation. Memory 32 may, in some examples, be described as anon-transitory or tangible computer-readable storage medium. In someexamples, memory 32 is a temporary memory, meaning that a primarypurpose of memory 32 is not long-term storage. Memory 32 may also, insome examples, be described as a volatile memory, meaning that memory 32does not maintain stored contents when the computer is turned off.Examples of volatile memories include random access memories (RAM),dynamic random access memories (DRAM), static random access memories(SRAM), and other forms of volatile memories known in the art. In someexamples, memory 32 may be used to store program instructions forexecution by processors 30. Memory 32 may be used by software orapplications running on computing device 2 (e.g., one or more ofapplications 46) to temporarily store information during programexecution.

Storage devices 36 may also include one or more non-transitory ortangible computer-readable storage media. Storage devices 36 may beconfigured to store larger amounts of information than memory 32.Storage devices 36 may further be configured for long-term storage ofinformation. In some examples, storage devices 36 may includenon-volatile storage elements. Examples of such non-volatile storageelements may include magnetic hard discs, optical discs, floppy discs,flash memories, or forms of electrically programmable memories (EPROM)or electrically erasable and programmable (EEPROM) memories.

Computing device 2 also includes a network interface 34. Computingdevice 2 may utilize network interface 34 to communicate with externaldevices via one or more networks, such as one or more wireless networks.Network interface 34 may be a network interface card, such as anEthernet card, an optical transceiver, a radio frequency transceiver, orany other type of device that can send and receive information. Examplesof such network interfaces may include Bluetooth®, 3G and WiFi® radiosin mobile computing devices as well as USB. Examples of such wirelessnetworks may include WiFi®, Bluetooth®, and 3G. In some examples,computing device 2 may utilize network interface 34 to wirelesslycommunicate with an external device (not shown) such as a server, mobilephone, or other networked computing device.

Computing device 2 may also include one or more input devices 38. Inputdevice 38 may be configured to receive input from a user throughtactile, audio, or video input. Examples of input device 38 may includea touch-sensitive screen, mouse, a keyboard, a voice responsive system,video camera, or any other type of device for detecting a command from auser.

One or more output devices 40 may also be included in computing device2, e.g., I/O device 12. Output device 40 may be configured to provideoutput to a user using tactile, audio, or video output. Output device 40may include a touch-sensitive screen, sound card, a video graphicsadapter card, or any other type of device for converting a signal intoan appropriate form understandable to humans or machines. Additionalexamples of output device 40 may include a speaker, a cathode ray tube(CRT) monitor, a liquid crystal display (LCD), or any other type ofdevice that can provide output to a user.

Computing device 2 may include one or more batteries or power sources42, which may be rechargeable and provide power to computing device 2.One or more power sources 42 may be a battery made from nickel-cadmium,lithium-ion, or any other suitable material. The one or more powersources 42 may be rechargeable and/or the device 2 can be powered via apower supply connection.

Computing device 2 may include operating system 44. Operating system 44may control the operation of components of computing device 2. Forexample, operating system 44 may facilitate the interaction ofapplication 46 or text entry application 8 with processors 30, memory32, network interface 34, storage device 36, input device 38, outputdevice 40, and battery 42.

Operating system 44 may additionally include user input module 6. Userinput module 6 may be executed as part of operating system 44. In othercases, user input module 6 may be implemented or executed by computingdevice 2. User input module 6 may process input, e.g., user input 18received from user 14 through one or more input devices 38.Alternatively, user input module 6 may receive input from a componentsuch as processors 30, memory 32, network interface 34, storage devices36, one or more output devices 40, battery 42, or operating system 44.In some cases, user input module 6 may perform additional processing onuser input 18. In other cases, user input module 6 may transmit input toan application, e.g. application 46 or text entry application 8, orother component in computing device 2.

Any applications, e.g. application 46 or text entry application 8,implemented within or executed by computing device 2 may be implementedor contained within, operable by, executed by, and/or beoperatively/communicatively coupled to components of computing device 2,e.g., processors 30, memory 32, network interface 34, and/or storagedevices 36. In one example, character recognition module 10 is executedon a server physically separate from computing device 2, and connectedto computing device 2 by a network connection via network interface 34.

FIG. 3 is a flow chart illustrating an example method 50 that may beperformed by a computing device to recognize a character correspondingto a touch input, in accordance with one or more aspects of the presentdisclosure. For example, method 50 may be performed by computing device2 shown in FIG. 1 or 2.

Method 50 includes receiving touch-based input relating to a sequence ofstrokes at a touch-based interface of a computing device, wherein afirst subset of the sequence of strokes corresponds to a first graphicalarea of the touch-based interface and a second subset of the sequence ofstrokes corresponds to a second graphical area of the touch-basedinterface that at least partially overlaps the first graphical area(52). These strokes will be discussed in greater detail below withrespect to FIGS. 4 and 5. Method 50 further includes displaying agraphical representation of the first subset of the sequence of strokeson an output device coupled to the computing device (53).

Method 50 further includes determining a confidence level that a firstcharacter approximately matches the first subset of the sequence ofstrokes, wherein the confidence level is of at least a first confidencethreshold (54). For example, character recognition module 10 may analyzethe first subset of the sequence of strokes to determine whether thefirst subset of strokes corresponds to a potential character. Characterrecognition module 10 may compare the first subset of strokes to a setof characters, for example, stored in reference database 11, and assigna rank or score for each character or for a subset of the set ofcharacters based at least in part on how likely the character matchesthe first subset of strokes, wherein the rank or score is related to theconfidence level.

In one example, character recognition module 10 may determine a measureof congruence with a first character. For example, when the shape of thefirst character approximately matches the shape of the first subset ofstrokes, the first character may be ranked or scored relatively highlyfor congruence over less congruent characters. When the shape of asecond character does not approximately match the shape of the firstsubset of strokes, the second character may not be ranked or scoredhighly for congruence. In this example, the first character may be givena higher ranking or score than the second character as a potential matchfor the first subset of strokes.

Method 50 may further include adjusting a display of the graphicalrepresentation (e.g., partially fading the graphical representation) ofthe first subset of the sequence of strokes based on the confidencelevel (56). In one example, the graphical representation of the firstsubset of the sequence of strokes may be adjusted to a greater extentbased on greater a confidence level. In another example, the graphicalrepresentation may not be faded until the confidence level that thefirst character corresponds to the first subset of the sequence ofstrokes is at least equal to or above a first confidence threshold. Inone example, fading the graphical representation based on the confidencelevel aids in clearing the output device for additional user input. Inone example, fading may be performed at a word level, for example, anentire word may be faded as a group. In some examples, fading may bedetermined based on a timeout period (e.g., strokes are faded a specifictime after entry). In some examples, a first stroke may be faded once athreshold number of strokes has been input after the first stroke.

Method 50 may also include providing the first character for processingby an application executing on the computing device when the confidencelevel is of at least a second confidence threshold, wherein theapplication is designed to process characters from touch-based input(58). In one example, the second confidence threshold is a selectedthreshold that indicates that a first sequence of strokes corresponds tothe first character. In one example, the second confidence threshold mayindicate a higher accuracy than the first confidence threshold. Inanother example, the second confidence threshold may be approximatelyequal to the first confidence threshold.

Other factors that character recognition module 10 may use to recognizeuser input 18 include vertical spacing between two strokes (e.g., adistance between two strokes in a first direction), horizontal spacingbetween two strokes (e.g., a distance between two strokes in a seconddirection orthogonal to the first direction), horizontal or verticalpositioning of a stroke (e.g., where a stroke is located on a touchscreen), crossing of strokes (e.g., where one stroke intersectsanother), the number of strokes in a subset of strokes, chronologicalorder in which the strokes were inputted, a combination of differentcharacters in a single stroke, previously recognized characters, words,or sentences, or any other suitable factor used in characterrecognition. Furthermore, segmentation of strokes may be based on any ofthe above enumerated factors. For example, when user 14 starts writingat a first side of touch-based interface 4 and reaches the oppositeside, and then starts writing again on the first side, the overlap withstrokes on the first side may indicate segmentation between characters.

Character recognition module 10 may select a character based at least inpart on any number of the foregoing factors. In one example, characterrecognition module 10 may assign a weight to each factor and mayselected a character based at least in part on a weighted average of thefactors. In one example, character recognition module 10 or otherapplication in computing device 2 may use minimum error rate training(“MERT”) to assign or modify a weight of a particular factor. MERT is amethod used to estimate weights assigned in a linear model such that anautomated evaluation criterion for measuring system performance candirectly be optimized in training. In other words, computing device 2may use MERT to improve the accuracy of handwriting recognition of user14 as user 14 uses computing device 2. In one example, partially fadingstrokes based on their confidence level may aid user 14 in training thecharacter recognition module 10. In some examples, MERT techniques areapplied to computing device 2 in a training mode of computing device 2.In other examples, MERT techniques are applied as user 14 enters userinput 18. Any corrections user 14 makes to the characters recognized bycharacter recognition module 10 may be used to improve the accuracy ofcharacter recognition module 10.

Once a character is recognized, method 50 may identify or provide thefirst character for processing by an application executing on thecomputing device, wherein the application is designed to processcharacters from touch-based input (56). For example, characterrecognition module 10 generates a signal corresponding to the firstcharacter for processing by text entry application 8, for example,displaying the first character at cursor 24. In another example, textentry application 8 may use the signal corresponding to the firstcharacter as a control input.

FIG. 4 is a conceptual diagram illustrating one example of a sequence ofstrokes of touch-based input 19-1 through 19-4 that may be recognized bya computing device executing a character recognition module, inaccordance with one or more aspects of the present disclosure. Forexample, user 14 handwrote the sequence of strokes 19-1 through 19-4using touch screen 60 of computing device 2. Touch screen 60 may displaya graphical representation of the sequence of strokes 19-1 through 19-4.

The sequence of strokes 19-1 through 19-4 may have been entered inchronological order from stroke 19-1 to stroke 19-4. As shown in FIG. 4,user 14 may have written the letter “H” as a first subset of thesequence of strokes, that is, strokes 19-1 through 19-3, in a firstgraphical area 62-1 of touch screen 60. User 14 may continue writingover the top of the first subset of the sequence of strokes, forexample, stroke 19-4 overlaps stroke 19-3. Stroke 19-4 is written in asecond graphical area 62-2 of the touch screen 60, wherein the secondgraphical area 62-2 overlaps the first graphical area 62-1. Characterrecognition module 10 may recognize characters inputted by user 14despite at least a portion of the characters overlapping each other.This allows user 14 to reuse areas of touch screen 60 without waitingfor character recognition module 10 to recognize previously writtenstrokes.

Character recognition module 10 may instruct display device 20 to alterthe display of a subset of strokes (e.g., fade the display of the subsetof strokes) based at least in part on a probability of an accuratedetermination. For example, the more likely the subset of strokes isaccurately recognized, the lighter the shade of an ink display. In oneexample, once character recognition module 10 determines a subset ofstrokes corresponds to a character having a ranking or score above athreshold confidence level, display device 20 stops displaying thosestrokes (for example, the strokes corresponding to the recognizedcharacter may fade out completely).

Character recognition module 10 may also detect two or more charactersin a single stroke, such as unrecognized input 28. Character recognitionmodule 10 may determine a boundary between one character and anotherwhen user input 18 connects the characters (for example, in cursivehandwriting). For example, character recognition module 10 maydifferentiate between the “e” and the “l” in stroke 19-4 based at leastin part on techniques described herein.

FIGS. 5A-5D are conceptual diagrams illustrating one example of asequence of strokes 70 inputted by a user that may be analyzed by acharacter recognition module, in accordance with one or more aspects ofthe present disclosure. In the example shown in FIGS. 5A-5D, a user 14wrote “Hello” in the form of the sequence of strokes 70, which includesstrokes 70-1 through 70-9. In FIGS. 5A-5D, strokes 70 are shown havinghorizontal offset for clarity; however, it is to be understood that someof strokes 70-1 through 70-9 may be written on top of other strokes 70-1through 70-9 (that is, some of strokes 70-1 through 70-9 may overlap).

In one example, character recognition module 10 may consider differentsubsets of the sequence of strokes 70 to determine which characters user14 intended to input. For example, user 14 chronologically inputs thesequence of strokes 70 to computing device 2 via touch-based interface4. FIGS. 5A-5D illustrate one example of how character recognitionmodule 10 may determine which strokes are in a first subset of strokesbased at least in part on reviewing different chronological subsets ofstrokes until a character is recognized from the strokes within thatsubset.

In FIG. 5A, character recognition module 10 may consider each stroke70-1 through 70-9 individually. That is, a subset of the sequence ofstrokes 70 contains a single stroke. Character recognition module 10 maylook at each stoke 70-1 through 70-9 and assign a score for eachapproximate match to a character. For example, character recognitionmodule 10 may find an approximate match for strokes 70-1, 70-3, 70-7,and 70-8 in capital and lower case of the letters “L” and “I,” as wellas the number 1. In such an example, without any prior user input 18recognized, character recognition module 10 may assign a score orranking to the potential matches based at least in part on the sequenceof stokes 70-1 through 70-9. In examples having previously recognizedcharacters, character recognition module 10 may additionally assignscores based at least in part on the previously recognized characters.

Additionally, for example, character recognition module 10 considersstrokes 70-2, 70-5, and 70-6 to potentially be a dash “-” or underscore“_” and may rank these potential results accordingly. However, in someexamples, because of stroke 70-6's relatively high vertical placement,character recognition module 10 may give “_” a relatively low score.Stroke 70-4 may be approximately matched as the capital letter “L” andassigned a high ranking Likewise, stroke 70-9 may be a capital orlowercase letter “O” or number “0.”

Character recognition module 10 may rank or score these potentialmatches based on their likelihood of accurately matching one or any ofthe characters (for example, based on previous or subsequent subsets ofstrokes, vertical positioning, size, etc.). A high ranking may be aranking that shows the character is more likely to be the intendedcharacter than a baseline or average. Comparatively, a low ranking maybe a ranking that shows the character is less likely to be the intendedcharacter than the baseline or average.

Character recognition module 10 may also consider subsets of strokes 70having two strokes, as in FIG. 5B. In some examples, the subsets ofstrokes 70 contain consecutive strokes (that is, strokes that occurrednext to each other in chronological order). In other examples, thesubsets of strokes 70 contain strokes that are not consecutive (forexample, a subset of strokes corresponding to a letter “I” may not beconsecutive, as user 14 may dot the “i” after completing other lettersof a word). For illustrative purposes, FIGS. 5A-5D show subsets ofstrokes 70 containing consecutive strokes.

Character recognition module 10 may consider the combination of eachstroke in the subset of strokes as a single character. For example, inFIG. 5B, a subset of strokes 70 containing strokes 70-2 and 70-3, aswell as 70-3 and 70-4, may potentially be the letter “t” or the symbol“+,” and may be ranked or scored by character recognition module 10.Some subsets of strokes 70, for example, 70-3 and 70-4, as well as 70-7and 70-8, may not have a potential match. In such an example, thosesubsets of strokes are assigned a low ranking or score, or none at all.

FIG. 5C shows an example of the subsets of strokes containing threeconsecutive strokes. In this example, character recognition module 10recognizes strokes 70-1 through 70-3 as potentially being a letter “H.”This recognition may be based on comparing the subset of strokes to adatabase of characters, or may be performed in another way. Therefore,the letter “H” may be given a high score or ranking for this subset ofstrokes. Similarly, strokes 70-4 through 70-6 correspond to a letter ‘E’and may be scored or ranked accordingly. Once character recognitionmodule 10 determines that a subset of strokes may be an “E,” characterrecognition module 10 may use that information to re-rank or re-scorepreviously ranked or scored characters. For example, characterrecognition module 10 may give “H” a higher ranking or score once “E” isdetected. Character recognition module 10 may increase the ranking of“H” because character recognition module 10 may consult a databasecontaining a dictionary which lists words beginning with “he.”

Likewise, FIG. 5D shows an example where the subsets of strokes 70contain four consecutive strokes. In some examples, characterrecognition module 10 may have a threshold number of strokes that may beconsidered for a character. In the example of FIG. 5D, characterrecognition module 10 may set a threshold level of the number of strokesat four. This may be because as the number of strokes in a subsetincreases, the likelihood that subset matches a particular characterdecreases. In this example, character recognition module 10 may not findany high ranking character matches.

Character recognition module 10 may consider some or all of the subsetsof strokes and their corresponding matches' rankings or scores inrecognizing user 14's input. For example, based on various factors,character recognition module 10 may compare subsets with each other, aswell as potential character matches within a subset. In some examples,character recognition module 10 maintains at least up to a maximumnumber of potential matches (for example, character recognition module10 stores twenty most probable potential matches for each subset ofstrokes). In other examples, a maximum number of potential matches maybe another number.

In one example, character recognition module 10 may compare differentscores or rankings of subsets for particular characters, and select asthe matching character that character which has the highest score forthat subset or character with a score above a selected threshold level.In another example, character recognition module 10 may access adictionary or grammar reference to identify and/or suggest a word basedat least in part on a determined sequence of characters. In one example,the character recognition module 10 determines that user input 18 inFIGS. 5A-5D is the word ‘Hello.’

Techniques described herein may be implemented, at least in part, inhardware, software, firmware, or any combination thereof. For example,various aspects of the described embodiments may be implemented withinone or more processors, including one or more microprocessors, digitalsignal processors (DSPs), application specific integrated circuits(ASICs), field programmable gate arrays (FPGAs), or any other equivalentintegrated or discrete logic circuitry, as well as any combinations ofsuch components. The term “processor” or “processing circuitry” maygenerally refer to any of the foregoing logic circuitry, alone or incombination with other logic circuitry, or any other equivalentcircuitry. A control unit including hardware may also perform one ormore of the techniques of this disclosure.

Such hardware, software, and firmware may be implemented within the samedevice or within separate devices to support the various techniquesdescribed herein. In addition, any of the described units, modules orcomponents may be implemented together or separately as discrete butinteroperable logic devices. Depiction of different features as modulesor units is intended to highlight different functional aspects and doesnot necessarily imply that such modules or units are realized byseparate hardware, firmware, or software components. Rather,functionality associated with one or more modules or units may beperformed by separate hardware, firmware, or software components, orintegrated within common or separate hardware, firmware, or softwarecomponents.

Techniques described herein may also be embodied or encoded in anarticle of manufacture including a computer-readable storage mediumencoded with instructions. Instructions embedded or encoded in anarticle of manufacture including an encoded computer-readable storagemedium, may cause one or more programmable processors, or otherprocessors, to implement one or more of the techniques described herein,such as when instructions included or encoded in the computer-readablestorage medium are executed by the one or more processors. Computerreadable storage media may include random access memory (RAM), read onlymemory (ROM), programmable read only memory (PROM), erasableprogrammable read only memory (EPROM), electronically erasableprogrammable read only memory (EEPROM), flash memory, a hard disk, acompact disc ROM (CD-ROM), a floppy disk, a cassette, magnetic media,optical media, or other computer readable media. In some examples, anarticle of manufacture may comprise one or more computer-readablestorage media.

In some examples, computer-readable storage media may comprisenon-transitory or tangible media. The term “non-transitory” may indicatethat the storage medium is not embodied in a carrier wave or apropagated signal. In certain examples, a non-transitory storage mediummay store data that can, over time, change (e.g., in RAM or cache).

Various aspects of the disclosure have been described. Aspects orfeatures of examples described herein may be combined with any otheraspect or feature described in another example. These and otherembodiments are within the scope of the following claims.

1. A method for recognizing characters, comprising: receivingtouch-based input relating to a sequence of strokes at a touch-basedinterface of a computing device, wherein a first subset of the sequenceof strokes corresponds to a first area of the touch-based interface anda second subset of the sequence of strokes corresponds to a second areaof the touch-based interface that at least partially overlaps the firstarea; displaying a graphical representation of the first subset of thesequence of strokes on an output device coupled to the computing device;determining a confidence level that a first character approximatelymatches the first subset of the sequence of strokes, wherein theconfidence level is of at least a first confidence threshold, furthercomprising: checking a combination of the first character and adetermined character against a language reference; ranking the firstcharacter based at least in part on approximate matches of thecombination of the first character and one or more previously determinedcharacters found in the language reference, wherein the ranking isrelated to the confidence level; and selecting the first character whenthe ranking is above a selected threshold level; altering the display ofthe graphical representation of the first subset of the sequence ofstrokes based on the confidence level; and providing the first characterfor processing by an application executing on the computing device whenthe confidence level is of at least a second confidence threshold,wherein the application is designed to process characters fromtouch-based input.
 2. The method of claim 1, wherein altering thedisplay of the graphical representation of the first subset of thesequence of strokes further comprises: ceasing to display the graphicalrepresentation of the first subset of the sequence of strokes when theconfidence level is of at least the second confidence threshold.
 3. Themethod of claim 1, wherein determining the confidence level that thefirst character approximately matches the first subset of the sequenceof strokes further comprises: comparing a graphical representation ofthe first subset of the sequence of strokes to one or more characters ofa set of characters; ranking the one or more characters based at leaston the comparison of the graphical representation to the one or morecharacters, wherein the rank is related to the confidence level; andselecting the one or more characters as the first character based atleast in part on the rank.
 4. The method of claim 3, wherein ranking isbased at least in part on how closely the graphical representationmatches the one or more characters.
 5. The method of claim 1, furthercomprising: determining that the second subset of the sequence ofstrokes corresponds to a second character; and generating the secondcharacter for processing by the application.
 6. The method of claim 5,further comprising: displaying the first character at a first locationin a textual display; and displaying the second character at a secondlocation in the textual display, wherein the second location is based inpart on a relationship between the first character and the secondcharacter.
 7. The method of claim 1, wherein the first area isapproximately the same as the second area.
 8. The method of claim 1,wherein determining the confidence level that the first characterapproximately matches the first subset of the sequence of strokesfurther comprises: arranging the sequence of strokes into achronological order based at least on when at least one stroke of thesequence of strokes was received at the touch-based interface; selectingat least a first stroke and comparing at least the first stroke to oneor more characters; and ranking the one or more characters based atleast in part on the comparison between the first stroke and the one ormore characters.
 9. The method of claim 8, further comprising: selectingthe first character from the one or more characters based at least onthe ranking of the one or more characters.
 10. The method of claim 9,further comprising: comparing at least one ranking corresponding to thefirst stroke with at least one ranking corresponding to the combinationof the first and second strokes; selecting one of at least the firststroke or the combination of the first and second strokes to be thesubset of the sequence of strokes based at least in part on thecomparison.
 11. The method of claim 1, further comprising: determiningwhich strokes of the sequence of strokes to include in the first subsetof the sequence of strokes based at least in part on vertical positionsof the strokes within the touch-based interface, timing informationrelating to when the strokes were received, vertical spacing between thestrokes, and horizontal spacing between the strokes.
 12. The method ofclaim 11, wherein the first subset of strokes contains less than orequal to a threshold level of number of strokes.
 13. The method of claim1, wherein altering the display of the graphical representation of thefirst subset of the sequence of strokes further comprises: fading thedisplay of the graphical representation of the first subset of thesequence of strokes.
 14. The method of claim 1, further comprising:displaying a graphical representation of the second subset of thesequence of strokes on the output device coupled to the computingdevice.
 15. The method of claim 1, wherein the sequence of strokes is afirst sequence of strokes and wherein the determined character is acharacter determined from a previously received touch-based inputrelating to a second sequence of strokes.
 16. The method of claim 1,wherein the first subset of the sequence of strokes comprises a firstcharacter or word and the second subset of the sequence of strokescomprises a second character or word.
 17. A non-transitorycomputer-readable medium comprising instructions for causing aprogrammable processor to perform operations comprising: receivingtouch-based input relating to a sequence of strokes at a touch-basedinterface of a computing device, wherein a first subset of the sequenceof strokes corresponds to a first graphical area of the touch-basedinterface and a second subset of the sequence of strokes corresponds toa second graphical area of the touch-based interface that at leastpartially overlaps the first graphical area; displaying a graphicalrepresentation of the first subset of the sequence of strokes on anoutput device coupled to the computing device; determining that thefirst subset of the sequence of strokes corresponds to a first characterby at least a first confidence threshold, further comprising: checking acombination of the first character and a determined character against alanguage reference; ranking the first character based at least in parton approximate matches of the combination of the first character andpreviously determined characters found in the language reference,wherein the ranking is related to the confidence level; and selectingthe first character when the ranking is above a selected thresholdlevel; altering the graphical representation of the first subset of thesequence of strokes based on the determination that the first subset ofthe sequence of strokes corresponds to the first character; andproviding the first character for processing by an application executingon the computing device, wherein the application is designed to processcharacters from touch-based input.
 18. A computing device, comprising:one or more processors; an input device to receive touch-based userinput of a sequence of strokes related to textual information, whereinthe sequence of strokes comprises a first subset of strokescorresponding to a first area of the input device and a second subset ofstrokes corresponding to a second area of the input device at leastpartially overlapping the first subset of strokes; means for determiningwhich strokes of the series of stroke fall into the first subset of thesequence of strokes and for determining that the first subset of thesequence of strokes corresponds to a first character, furthercomprising: means for checking a combination of the first character anda determined character against a language reference; means for rankingthe first character based at least in part on approximate matches of thecombination of the first character and previously determined charactersfound in the language reference, wherein the ranking is related to theconfidence level; and means for selecting the first character when theranking is above a selected threshold level; an output device to displaya graphical representation of the first subset of the sequence ofstrokes, wherein the output device alters the graphical representationbased on the determination that the first subset of the sequence ofstrokes corresponds to the first character; wherein the output devicefurther output the first character.